Parallel static and dynamic multi-constraint graph partitioning

2002 ◽  
Vol 14 (3) ◽  
pp. 219-240 ◽  
Author(s):  
Kirk Schloegel ◽  
George Karypis ◽  
Vipin Kumar
Keyword(s):  
Graph Partitioning ◽  
Constraint Graph

scholarly journals An exact approach for the multi-constraint graph partitioning problem

2020 ◽  
Vol 8 (3-4) ◽  
pp. 289-308 ◽  
Author(s):  
Diego Recalde ◽  
Ramiro Torres ◽  
Polo Vaca
Keyword(s):  
Graph Partitioning ◽  
Graph Partitioning Problem ◽  
Exact Approach ◽  
Constraint Graph ◽  
Partitioning Problem

scholarly journals Parallel Multilevel Algorithms for Multi-constraint Graph Partitioning

2000 ◽  
pp. 296-310 ◽  
Author(s):  
Kirk Schloegel ◽  
George Karypis ◽  
Vipin Kumar
Keyword(s):  
Graph Partitioning ◽  
Multilevel Algorithms ◽  
Constraint Graph

FINAL VERSION.pdf

2019 ◽  
Author(s):  
Nasir Saeed ◽  
Mohamed-Slim Alouini ◽  
Tareq Y. Al-Naffouri
Keyword(s):  
Graph Partitioning ◽  
Three Dimensional ◽  
Smart Objects ◽  
Localization Technique ◽  
Optical Internet ◽  
Spectral Graph ◽  
Accurate Localization ◽  
Spectral Graph Partitioning ◽  
Link Connectivity

<div>Localization is a fundamental task for optical internet</div><div>of underwater things (O-IoUT) to enable various applications</div><div>such as data tagging, routing, navigation, and maintaining link connectivity. The accuracy of the localization techniques for OIoUT greatly relies on the location of the anchors. Therefore, recently localization techniques for O-IoUT which optimize the anchor’s location are proposed. However, optimization of anchors location for all the smart objects in the network is not a useful solution. Indeed, in a network of densely populated smart objects, the data collected by some sensors are more valuable than the data collected from other sensors. Therefore, in this paper, we propose a three-dimensional accurate localization technique by optimizing the anchor’s location for a set of smart objects. Spectral graph partitioning is used to select the set of valuable</div><div>sensors.</div>

Mathematics of networks

2018 ◽  
Author(s):  
Mark Newman
Keyword(s):  
Random Walks ◽  
Adjacency Matrix ◽  
Graph Partitioning ◽  
Dynamic Networks ◽  
Graph Laplacian ◽  
Network Visualization ◽  
Final Part ◽  
Bipartite Networks ◽  
Component Structure ◽  
Basic Properties

An introduction to the mathematical tools used in the study of networks. Topics discussed include: the adjacency matrix; weighted, directed, acyclic, and bipartite networks; multilayer and dynamic networks; trees; planar networks. Some basic properties of networks are then discussed, including degrees, density and sparsity, paths on networks, component structure, and connectivity and cut sets. The final part of the chapter focuses on the graph Laplacian and its applications to network visualization, graph partitioning, the theory of random walks, and other problems.

A Method of Equipment Disassembly Path Planning Based on Directed Constraint Graph Disassembly Sequence

2020 ◽  
Author(s):  
Yang Cao ◽  
Hongtian Liu ◽  
Chao Song ◽  
Hongwei Wu ◽  
Dongjun Wang ◽  
...  
Keyword(s):  
Path Planning ◽  
Constraint Graph ◽  
Disassembly Sequence
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